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.
Using transcriptomic profiling and CRISPR/Cas9 mutagenesis in larval zebrafish, this study identifies *sim1a* as a candidate gene for strabismus that impairs eye movement via vestibulo-ocular reflex dysfunction without affecting motor neuron numbers, while establishing a pipeline for discovering genes underlying ocular motor diseases.
This study demonstrates that while pulsed transcutaneous auricular vagus nerve stimulation (taVNS) can elicit pupil dilation in intermixed experimental designs, the effect's dependence on sham location and lack of respiratory phase modulation challenge the assumption that it is mediated by the vagal afferent pathway.
Using brainstem-optimized fMRI, this study demonstrates that task-dependent modulation of stretch-evoked motor responses is associated with measurable, instruction-specific activation changes in human brainstem reticulospinal regions, confirming their role in rapid feedback control.
By integrating pharmacodynamic profiles with receptor density data from PET and autoradiography, this study maps the whole-brain distribution of classic hallucinogens and ketamine, revealing that their rapid antidepressant effects are driven by strong action in emotion-processing regions, particularly association cortices and supragranular layers.
This study presents a zero-parameter walk-sum framework that analytically derives frequency-dependent brain communication architecture directly from structural connectome topology, successfully predicting spatial coupling patterns across diverse MEG and intracranial EEG datasets while revealing how anesthesia and schizophrenia alter these structural channels.
The paper introduces HeteroRC, a biologically inspired and interpretable heterogeneous reservoir computing framework that outperforms conventional linear decoders and complex neural networks by effectively extracting latent nonlinear, non-phase-locked, and "activity-silent" information from dynamic neural responses without requiring manual feature engineering.
This study demonstrates that Insulin-like Growth Factor 1 (IGF-1) exerts region-specific effects on glutamate receptor activity by inhibiting AMPA receptor-mediated calcium responses in neocortical neurons while enhancing them in hippocampal neurons, suggesting a potential neuroprotective role against excitotoxicity in the neocortex that may be compromised in conditions like insulin resistance.
This study reveals that rod photoreceptor health critically depends on the cytosolic enzyme GOT1 to prevent toxic NADH accumulation, whereas the mitochondrial enzyme GOT2 is downregulated during stress as a protective mechanism, identifying reductive stress as a key driver of degeneration and GOT2 as a novel therapeutic target.
This study demonstrates that acute exposure to beta-sheet-containing tau oligomers reversibly impairs sharp-wave ripple oscillations in both mouse and human hippocampal slices, with species-specific effects on ripple parameters, establishing a high-throughput ex vivo model for investigating Alzheimer's disease mechanisms and screening therapeutics.
This study introduces a novel data-driven approach to map explicitly nonlinear fMRI connectivity in human infants, revealing that these nonlinear networks uncover complementary developmental trajectories for key brain systems—such as sensorimotor and default mode networks—that remain hidden when relying solely on traditional linear methods.