1296 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.
The paper introduces Long-Horizon Associative Learning (L-HAL), a unified, biologically grounded framework that uses a single neural mechanism with graded temporal overlap to explain diverse statistical learning phenomena across multiple temporal scales, from local transitions to complex network structures.
A harmonized mega-analysis of fMRI data challenges the prevailing view of strict functional segregation within the extended amygdala, revealing that both the central nucleus and bed nucleus of the stria terminalis respond similarly to threat regardless of temporal certainty, while frontocortical regions specifically process uncertain threats.
This paper demonstrates that fine-tuning pre-trained chemical foundation models via a novel LoRA-based approach (LORAX) is necessary to generate superior, olfaction-specific odorant representations that outperform both classical hand-designed features and unadapted foundation model embeddings in predicting odorant-receptor binding.
By combining high-resolution videography with a dedicated computer-vision pipeline, this study reveals that cephalopod chromatophores are controlled by complex, overlapping motor units innervated by approximately four neurons per organ, enabling the formation of virtual chromatophores and diverse geometric patterns essential for dynamic camouflage.
This study identifies a predictive noradrenergic-astroglial circuit in zebrafish that integrates sensory detection of hypoxia with efference copies of motor actions to trigger preemptive behavioral adaptations, thereby averting metabolic crisis before oxygen depletion occurs.
This study demonstrates that polarization-sensitive optical coherence tomography can detect longitudinal structural changes in the optic nerve head of mouse models for Alzheimer's disease and neuronal degeneration, establishing it as a potential preclinical biomarker for these pathologies.
The authors present Photon-Resolved Excitation-Denoised (PRED) three-photon imaging, a novel technique that overcomes previous limitations in speed, signal-to-noise ratio, and motion artifacts to enable high-speed, high-fidelity functional imaging of neuronal activity in deep brain regions of awake, behaving mice.
This study introduces an explainable machine learning framework using Importance Inversion Transfer to identify eight stable, shared neuroanatomical features across Alzheimer's and Parkinson's diseases, supporting the Neurodegenerative Elderly Syndrome concept and offering a paradigm for early, system-level diagnosis.
Through five psychophysical experiments involving degraded tactile feedback, this study demonstrates that the human tactile system reduces complex dynamic touch signals to a single stable perceptual feature—total spectral energy—which governs judgments of hardness and material identity more effectively than waveform details or dominant frequency.
By leveraging a 10.5 Tesla scanner to achieve sub-millimeter resolution, this study demonstrates the potential of ultrahigh field fMRI to non-invasively resolve cortical laminar activity and bridge the gap with invasive imaging, while acknowledging the significant technical challenges that must be overcome to fully realize these benefits.