1795 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.
Three virtual reality experiments demonstrate that the discomfort caused by an angry face is not solely due to perceived anger, but is significantly driven by interpersonal distance, direct gaze, and the presence of a human-like face rather than just the emotional expression itself.
This paper presents a lightweight, low-cost, multichannel magnetoencephalography system that utilizes active shielding and software-based spatial filtering to achieve high-quality brain imaging without the need for a traditional magnetically shielded room, thereby democratizing access to this advanced neuroimaging technology.
By recording from four frontal cortical regions in monkeys solving a spatial maze, this study reveals that goal-directed behavior is supported by a distributed network where distinct areas partially specialize in encoding specific task variables (such as state, goal, and move) while collectively maintaining an abstract, hierarchical code of problem structure.
This study introduces neural prediction decorrelation (NPD), a method that synthesizes stimuli to reveal that adversarially robust deep neural networks significantly outperform standard models in predicting human auditory cortex responses across all regions, a superiority that remains undetectable when using only natural sounds.
This study demonstrates that a multi-modal ensemble combining pose-based and EEG-based classifiers significantly improves the prediction of table tennis players' attack intentions compared to unimodal approaches, offering promising applications for sports neurofeedback and neural prosthetics.
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.