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.
This paper presents a biologically constrained computational model of zebra finch song learning demonstrating that a dual-pathway architecture, combining a volatile basal ganglia reinforcement learning loop with a consolidating cortical motor pathway, enables robust sensorimotor learning by effectively navigating non-convex performance landscapes and escaping local optima.
This study demonstrates that individuals with higher baseline vestibulomotor weighting are more susceptible to cybersickness in virtual reality, and while their vestibular contributions decrease during exposure as an adaptive response, this reweighting is insufficient to prevent postural instability and symptom progression.
This study demonstrates that covert attention can be directed toward afterimages, as evidenced by pupil size tracking the perceived brightness of attended negative afterimages even in the absence of physical stimuli, thereby suggesting that the distinction between external and internal attention is a continuum rather than a strict dichotomy.
This paper demonstrates that evolutionary optimization acts as a crucial inductive bias that pre-conditions artificial neural networks, enabling them to exhibit unique latent learning dynamics and achieve rapid fine-tuning to optimal performance with significantly less data compared to randomly initialized networks.
This study demonstrates that rhythmic motor activity, such as finger tapping or transcranial alternating current stimulation, can modulate auditory attentional sampling by alleviating attentional blinks when resources are scarce, thereby revealing the motor system as an active, resource-dependent regulator of cognitive processes.
Using longitudinal two-photon calcium imaging in the frontal cortex, this study reveals that apical tuft dendrites of layer 5 neurons encode sensorimotor information distinct from somatic outputs, specifically tracking sensory cues and corrective actions while exhibiting unique plasticity during motor skill learning.
This study demonstrates that in the zebrafish olfactory memory network, behavioral learning enhances odor discrimination not through attractor dynamics but by optimizing the geometric separation and capacity of neural manifolds, thereby linking manifold structure directly to sensory and semantic processing.
This study demonstrates that neurons in the dorsomedial striatum of mice encode patch foraging decisions through a reward-reset, accumulation-to-threshold mechanism that integrates elapsed time since the last reward and environmental reward rates to determine when to abandon a depleting resource.
This study demonstrates that distinct subnetworks within the default mode network differentially support emotional memory recall, with the dorsomedial subnetwork encoding emotional valence and the medial temporal subnetwork facilitating perceptual specificity.
This study demonstrates that utilizing a 10.5T ultrahigh-field fMRI system enables unprecedented 0.5 mm isotropic resolution imaging of the human hippocampus, overcoming historical signal limitations to facilitate the investigation of functional microcircuits and high-precision clinical diagnostics.