1519 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 sleep supports memory consolidation and emotional regulation through dissociable mechanisms, where NREM sleep reactivates memories during slow oscillation-spindle complexes to strengthen temporal details, while REM sleep reactivates memories during phasic eye movements to reduce negative affect.
This study reveals that behavioral adaptation during cognitive-motor dual-tasking evolves dynamically within a session, with healthy older and younger adults achieving successful stabilization through distinct continuous and discrete whole-brain network reorganization patterns despite following different initial performance trajectories.
This study proposes an improved Hodgkin-Huxley framework that models ionic conductances as lognormal distributions derived from stochastic ion transit times and describes action potentials through a four-state transition paradigm, enabling more accurate estimation of physiological parameters from experimental data.
This study establishes that neural decoding gains are not absolute but depend critically on task context, temporal boundaries, and correct trial pairing, necessitating rigorous, model-relative reporting standards to distinguish true neural contributions from artifacts of data structure.
This paper proposes a biologically constrained cortico-subcortical circuit model that implements multi-head self-attention mechanisms through specific thalamo-cortical projections and pyramidal cell interactions, providing a neural substrate for mammalian cognitive performance that aligns with human intracranial recordings.
This paper presents a low-cost, modular, and open-source hardware and software platform that simplifies head-fixed rodent decision-making tasks by automating training to reduce experimenter labor and lower the barrier to entry for neuroscience research.
This paper proposes a continuous attractor neural network model that implements decision-making by integrating complementary ramping and sequential neural codes within a Laplace-domain framework, successfully reproducing both the behavioral statistics of diffusion decision models and the heterogeneous neural dynamics observed in biological systems.
This study demonstrates that the PEDF/PEDF-R signaling axis is essential for maintaining retinal phospholipid homeostasis, thereby ensuring photoreceptor survival, proper synaptic connectivity, and visual function.
By training recurrent neural networks with varying degrees of spatial constraints on a working-memory task, this study demonstrates that only networks embedding the brain's physical geometry can successfully predict empirical fMRI activity and develop brain-like topological features, revealing that physical geometry and cognitive inputs play distinct, complementary roles in shaping emergent brain dynamics.
This quasi-experimental study demonstrates that a brief, personalized training program (NExT-U) significantly improves specific executive functions, such as conscious behavior regulation and emotional regulation, in Cuban university students, thereby confirming cognitive plasticity in young adults.