1541 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.
Through two preregistered experiments and computational modeling, this study demonstrates that individuals can maintain both cognitive and motor performance under painful stimulation by actively mobilizing increased effort, a compensatory mechanism where subjective pain drives effort expenditure rather than stimulus intensity alone.
This study demonstrates that NRXN1 exhibits gene-dosage sensitivity, where bi-allelic deletions in exon 19 cause severe molecular, synaptic, and functional deficits in iPSC-derived neurons, whereas mono-allelic deletions result in only modest phenotypic changes.
This study demonstrates that high-resolution cardiac contractility, measured via trans-radial electrical bioimpedance velocimetry (TREV), serves as a superior physiological marker for linking sympathetic nervous system activity to neural modulation in specific brain regions, emotional intensity, and adaptive motor responses during threat anticipation compared to traditional skin conductance measures.
This study demonstrates that the loss of the chromatin remodeler Brg1 increases seizure susceptibility in zebrafish by selectively disrupting the GABAergic inhibitory system, a mechanism that can be mitigated by pharmacological enhancement of GABA levels or treatment with active vitamin B6.
In a sham-controlled study of 42 participants, theta-otDCS over the left posterior parietal cortex selectively improved object-location memory, with the magnitude of these effects varying significantly based on individual cognitive profiles through both magnification (benefiting faster processors) and compensation (benefiting those with lower mnemonic binding or reasoning abilities) mechanisms.
This paper proposes and validates an optimized multivariate temporal response function (mTRF) framework that integrates cyclic permutation, improved artifact rejection, and drift mitigation to effectively isolate distinct neural responses to partially dependent acoustic and phonetic speech features in EEG data.
This paper introduces VECTR-Clasp, an open-source, machine-learning framework that integrates DeepLabCut and SimBA to transform traditional categorical hind-limb clasping assessments into continuous, vector-based kinematic analyses, thereby revealing subtle motor microphenotypes in Cdkl5-deficient mice that are undetectable by standard scoring methods.
This study reveals that while alpha power correlates positively with microstructural features like myelin and iron across brain regions, it correlates negatively with these same features across individuals, suggesting that excitatory and inhibitory mechanisms drive intra- versus inter-individual variability in brain function, respectively.
This study demonstrates that a specific subpopulation of neutrophils expressing Il-4 promotes spinal cord regeneration in larval zebrafish by suppressing Il-1{beta}-mediated inflammation in macrophages and microglia, thereby ensuring successful anatomical and functional recovery.
This study demonstrates that tactile suppression during movement is not a fixed gating mechanism but rather a consequence of optimal, dynamic state estimation where the nervous system continuously adjusts its reliance on internal predictions versus noisy sensory feedback based on the level of uncertainty.