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 study demonstrates that while graph neural networks can achieve high autism classification accuracy on multisite fMRI data by leveraging cohort-specific context and supervision, they fail to generalize to unseen acquisition sites, highlighting the critical need for rigorous leave-one-site-out evaluation to distinguish between cohort-conditioned performance and true generalization.
This paper demonstrates that in competitive spiking networks, replacing fixed lateral inhibition with plastic homeostatic rules requires an "inhibitory budget matching" constraint to conserve total inhibitory drive, a principle that ensures network stability and preserves learning performance while allowing local inhibitory weights to adapt.
This paper proposes and validates a Bayesian-inspired framework for sequential decision-making, demonstrating that humans efficiently solve complex problems by integrating costly forward planning with task-specific preferences that act as state-dependent priors, weighted by their uncertainty to guide behavior when planning is computationally infeasible.
This study demonstrates that the vestibular control of posture deviates from Weber's law, as balance discrimination thresholds increase sublinearly with electrical stimulation amplitude due to specific, frequency-independent changes in response gain and signal-dependent variability.
This study identifies the T1R2/T1R3 heterodimer as a human-specific receptor that detects the Alzheimer's disease-associated reduction in the Aβ42/40 ratio, triggering neuronal hyperexcitability through voltage-gated sodium currents and offering a novel therapeutic target for early intervention.
This study reveals that the rapid and lasting suppression of thirst upon drinking is not caused by immediate rehydration but is instead a learned, predictive signal triggered by the oral passage of water that inhibits thirst-promoting neurons.
This study introduces a "change-point oddball" protocol that demonstrates pupil-linked arousal signatures of Bayesian belief updating in response to unpredictable environmental changes, establishing a passive, no-report method for investigating adaptive learning across species and clinical populations.
This paper introduces ROVER-dMRI, a unified rotating-view acquisition and super-resolution reconstruction framework that leverages implicit neural representations and physics-informed modeling to achieve high-SNR, whole-brain mesoscale diffusion MRI in clinically feasible scan times, outperforming state-of-the-art methods in resolution and efficiency.
This paper introduces a robust computational framework that overcomes the limitations of existing methods by dynamically compensating for electrode displacement and MUAP variations to enable reliable longitudinal tracking of individual motor units, thereby enhancing the sensitivity of neurophysiological assessments for studying neuromuscular plasticity and disease progression.
This study demonstrates that while reversible inhibition of medial septum interneurons initially abolishes the acquisition of new place-reward associations, repeated training in a stable environment allows mice to overcome this deficit by shifting from a hippocampus-dependent spatial strategy to a non-hippocampal visual pattern-matching solution.