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 establishes the first comprehensive genetic maps of human cortical sulcal complexity by analyzing rare variants in neurogenetic syndromes and common variants in a large UK Biobank cohort, thereby revealing shared genetic mechanisms, heritability patterns, and prenatal gene expression links that illuminate the developmental pathways of cortical folding in both health and disease.
This systematic review of 37 EEG studies establishes that auditory rise time prolongation generally reduces the amplitude and increases the latency of event-related potential components, while highlighting how these neural markers vary based on stimulus characteristics, participant age, and clinical status.
This study introduces a novel two-stage Pavlovian-instrumental transfer paradigm that demonstrates single-lever PIT is primarily driven by flexible, model-based learning mechanisms rather than automatic model-free processes, and reveals that these cognitive strategies are selectively impaired by mind wandering.
This study demonstrates that BOLD-induced linewidth changes cause a significant (~1%) overestimation of metabolic changes in functional MRS at both 3T and 7T, but shows that this bias can be effectively reduced to below 0.2% by implementing explicit BOLD lineshape correction or direct modeling in the analysis pipeline.
This study demonstrates that while optogenetic stimulation of retinal ganglion cells produces encoding differences compared to natural photoreceptor activation, applying specific image modifications such as thresholding, scaling, and spatial filtering can effectively restore more natural-like neural responses to support future therapeutic applications for blindness.
This paper proposes a neurally plausible model demonstrating that spatial navigation architectures, specifically those involving grid cells, can construct universal cognitive maps to support domain-general abstract reasoning tasks such as analogy making and perspective taking.
This paper constructs a neural network model for the fruit fly head direction system that reconciles connectome-derived structural constraints with continuous attractor dynamics, revealing that cell-type-specific synaptic rescaling can compensate for connectivity variations to enable robust spatial navigation.
This study utilized SSVEPs to demonstrate that a two-stage contrast gain-control model incorporating parallel monocular channels, but not necessarily phase selectivity, effectively explains neural responses to binocular in-phase and anti-phase stimuli.
This study identifies a pair of dopaminergic neurons (DA-WED) in Drosophila that link mechanical threat processing to cardiac deceleration and demonstrate that this specific cardiac modulation actively promotes defensive locomotor behavior.
This paper proposes an efficient computing theory for prefrontal cortex that resolves conflicting neural coding schemes in structured working memory tasks by demonstrating that contextual and compositional representations are optimal extremes on a spectrum determined by the statistical correlations of task elements.