1313 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 naturalistic movie watching engages a dual brain connectome architecture comprising a conserved sensory-association backbone for stable integration and flexible, stimulus-dependent hubs in higher-order regions that mediate dynamic information processing across distributed cortical systems.
This study demonstrates that arousal states significantly alter the switching rates of specific brain networks, particularly involving thalamic subregions, and that these dynamic changes moderate cognitive performance on relational processing tasks.
This study presents a single-cell transcriptomic analysis of pediatric refractory epilepsy patients in Colombia, revealing glia-driven synaptic dysregulation, neuroinflammatory mechanisms, and structural variants that offer new insights for diagnosis and treatment strategies.
This study demonstrates that applying anti-phase theta dual-tACS over the right temporo-parietal junction (rTPJ) significantly reduces the subjective feeling of joint agency in dyads performing an alternating tapping task, likely by impairing coordination efficiency while maintaining the overall 180-degree alternation structure.
This paper proposes a Deep Recurrent Q-Learning model that successfully replicates the behavioral dynamics of cognitive flexibility in task-switching scenarios by learning to update internal belief states and action preferences without requiring explicit cues or synaptic changes during execution, thereby challenging the view that Reinforcement Learning is unsuitable for modeling such processes.
This study demonstrates that GABAergic inhibition differentially recruits distinct dentate gyrus interneuron populations through feedforward and feedback mechanisms to tightly gate lateral entorhinal cortex inputs, thereby maintaining sparse granule cell activity essential for hippocampal pattern separation.
By leveraging a large-scale fMRI dataset to overcome signal artifacts, this study reveals that the anterior temporal lobe contains three distinct visual category preference profiles—differing in object versus scene selectivity and hemispheric bias—that exhibit a patchy spatial organization and dissociable functional connectivity patterns, thereby extending category sensitivity to the apex of the ventral visual stream.
This study demonstrates that disrupting FOXO4 function through knockout confers neuroprotection against oxidative stress and ischemia-reperfusion injury by reducing neuronal death, infarct volume, and neuroinflammation while improving survival and functional recovery.
This paper introduces a gaze-aware encoding model that integrates eye-tracking data with CNN features to effectively predict brain activity during naturalistic, free-viewing fMRI, achieving performance comparable to conventional models with significantly fewer parameters while enabling more ecologically valid neuroscience research.
This paper proposes a hierarchical neural circuit theory that dynamically implements divisive normalization via feedback connections, analytically deriving spectral signatures and predicting that feedback strength modulates inter-areal communication within a low-dimensional subspace while dictating dynamic functional connectivity across cortical areas.