1527 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 chemogenetic activation of Gi-coupled G-protein-coupled receptors in temporal cortex astrocytes specifically enhances fear memory retrieval by attenuating cue-evoked calcium transients, thereby modulating sensory cue processing to drive defensive behaviors.
This study demonstrates that prenatal exposure to a native language tunes newborns' brain dynamics toward a critical state, enhancing network flexibility and temporal correlations specifically in response to familiar linguistic patterns while remaining largely insensitive to rhythmically dissimilar languages.
This study demonstrates that systemic inflammation in psoriasis disrupts conserved thalamostriatal circuitry across humans and mice, directly driving depressive symptoms like anhedonia and fatigue, thereby identifying this neural pathway as a key therapeutic target for inflammation-related depression.
This study reveals that neural dynamics across the ventral visual stream follow a unified hierarchical motif where representations shift over time along a complexity axis driven by local recurrence, a phenomenon that current state-of-the-art dynamic models fail to replicate.
This study introduces a "Caring Attributions task" and demonstrates through behavioral modeling and EEG analysis that humans infer whether others are caring or uncaring using a novel "valence-partitioned temporal-difference Bayesian" (TD-Bayes) mechanism, which features distinct neural representations for positive and negative attributions that outperform previous associative learning models.
While confirming the presence of cellular senescence markers in a mouse model of focal cortical dysplasia, this study demonstrates that dasatinib-quercetin treatment reduces these markers without inducing senolysis or modifying seizure phenotypes, thereby challenging previous findings on the therapy's efficacy in this context.
This paper proposes a biologically plausible Equilibrium Propagation framework for Leaky Integrate-and-Fire spiking neural networks that utilizes a predictive learning rule instead of STDP, achieving competitive image classification accuracy comparable to backpropagation while exhibiting distinct, more persistent hidden-layer activity patterns.
This study demonstrates that while the recreational-to-habitual shift in psychostimulant use is an economic demand parameter capable of predicting consumption under price-constrained conditions, it is unrelated to drug intake levels under normal and punishment conditions.
By comparing neural responses to thousands of natural images in both humans and macaques, this study reveals a shared high-dimensional object space in the inferotemporal cortex while also identifying systematic species-specific asymmetries in how visual features and conceptual categories are represented.
This study proposes a computational hypothesis that the normal adolescent processes of synaptic pruning and myelination create dominant neural attractors for strongly encoded, emotionally salient memories, thereby increasing vulnerability to psychiatric disorders such as OCD, depression, and PTSD.