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 study demonstrates that engineering neural stem cells with a chimeric antigen receptor targeting integrin αvβ3 enhances their retention and dispersion within peri-infarct tissue, leading to improved vascular integrity, reduced inflammation, and greater regenerative potential in a mouse model of stroke.
Although task learnability did not generally alter reward positivity (RewP) amplitudes, restricting the analysis to high performers revealed that individuals with low reward responsiveness exhibited enhanced RewP specifically in learnable tasks, highlighting a critical interaction between contextual factors and individual differences in reward processing.
Using invasive human brain recordings from 16 participants, this study demonstrates that the specific shape of each individual breath is tightly coupled with the corresponding cycle-by-cycle waveform of neural oscillations across limbic and cortical forebrain regions, revealing a richer and more temporally precise brain-body interaction than previously appreciated.
This study of the BioFIND cohort reveals that Parkinson's disease is associated with altered glycosphingolipid metabolism and elevated GPNMB levels in plasma and cerebrospinal fluid, with significant sex-based differences and correlations to alpha-synuclein, suggesting these molecules serve as interconnected biomarkers of lipid pathology in PD.
Using CRISPR-Cas9-edited iPSC-derived brain cells, this study demonstrates that while PSEN1 and PSEN2 are both catalytic subunits of the {gamma}-secretase complex, they perform distinct and non-redundant functions, with PSEN2 knockout specifically disrupting the endo-lysosomal system without significantly affecting A{beta} generation or Nicastrin maturation, unlike PSEN1 knockout.
This study validates that aging is associated with a shift toward fine-scale entropy and specific spectral changes in the brain, while demonstrating that these patterns diverge by sex and that entropy-based measures capture unique aspects of temporal organization not reflected by spectral power alone.
This study demonstrates that oscillating hypercapnia temporarily enhances the clearance of neural proteins from the brain to the blood and reduces cognitive interference in both healthy individuals and those with chronic traumatic brain injury, suggesting a potential therapeutic mechanism for combating pathological protein aggregation through atrophy-moderated glymphatic flow.
This study demonstrates that as walking speed increases, humans transition from a discrete-dominated, less smooth movement regime with fewer muscle synergies to a more stable, rhythmic pattern characterized by higher kinematic smoothness and increased neuromuscular dimensionality, with a critical transition zone occurring around 3–3.5 km/h.
This study demonstrates that pathological cortico-STN beta coupling in Parkinson's disease is exclusively confined to brief beta burst epochs rather than being sustained during non-burst periods, suggesting that adaptive neuromodulation strategies should target these transient events.
This paper proposes a six-layer computational framework that models coupled neural oscillator networks as analog RLC circuits, demonstrating how subthreshold resonance, phase-based binding, and tunable impedance landscapes enable memory, pattern completion, and multiplexed computation while bridging the gap between linear electrical descriptions and nonlinear attractor dynamics.