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 reveals that distinct subpopulations within the monkey subthalamic nucleus differentially encode sensory evidence, reward expectations, and decision-related dynamics during complex reward-biased decision-making, thereby delineating their specialized roles in forming and evaluating choices.
This study demonstrates that cannabidiol (CBD) reverses age-associated cognitive decline in mice by restoring reduced endocannabinoid signaling, thereby normalizing microglial inflammation and neurotransmitter balance in the medial prefrontal cortex.
This study demonstrates that the relationship between attentional lapses and voluntary task switching is capacity-dependent, with lower-working-memory individuals tending to switch tasks following lapses due to goal competition, while higher-capacity individuals switch from focused states, suggesting that external task structures can specifically scaffold goal maintenance for those with lower capacity.
This study proposes a novel automated diagnosis scheme for schizophrenia that achieves 100% accuracy in distinguishing patients from healthy individuals by extracting and selecting time-frequency domain features from EEG signals and classifying them using various machine learning algorithms.
This double-blind, active-placebo-controlled study demonstrates that neurofeedback engages frequency-specific cortical mechanisms where reward-locked desynchronization drives durable plasticity only when supported by distinct, frequency-dependent circuit dynamics, as evidenced by a double dissociation between SMR and Beta training outcomes.
This study demonstrates that hybrid virtual reality, which pairs real object interaction with virtual visual feedback, successfully reproduces the hallmark behaviors of real-world dexterous object lifting, thereby establishing a valid experimental framework for investigating the role of proprioceptive reliability in skilled motor control.
This paper presents the first major component of the NIH BRAIN Initiative's Cell Atlas Network: a standardized, cross-species, multimodal atlas of the basal ganglia that integrates transcriptomic, epigenomic, and spatial data to establish a unified, FAIR framework for classifying brain cell types and enabling comparative neuroscience across humans, macaques, marmosets, and mice.
This study demonstrates that LAMP2 deficiency in a Xenopus tropicalis model of Danon disease causes synapse-specific alterations in autophagy, particularly in photoreceptor and olfactory sensory neuron terminals, which likely underlie the disorder's visual and cognitive impairments.
This study demonstrates that cognitive vergence and pupillary temporal dynamics during a visual oddball task serve as non-invasive functional oculomotor signatures capable of distinguishing between A+T+ and A-T+ biological profiles in individuals with mild cognitive impairment.
This study demonstrates that while hippocampal responses to event boundaries occur regardless of global brain state, the interplay between large-scale network dynamics (specifically shifts toward the Task-Positive Network) and event segmentation is critical for predicting subsequent memory for narrative content.