Neuroscience · Life Sciences
Neurons & Cognition
The newest papers in Neurons & Cognition that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
163 papers, from 31 August 2026 to 5 November 2026: 140 arXiv preprints and 23 OpenAlex records.
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Newest papers, page 6
Which Attention Heads are like the Human Head? Not the Ones that Compute
Brain-AI alignment is often interpreted as a sign that model and brain perform similar computations.Traversing the solution space of neural networks with Hessian Null Space Continuation
On a single task, deep networks can learn many solutions, depending on their optimizer, training data, architecture, and hyperparameters.Embodiment-aware control by inference over the operator: a simulation study
Teleoperation systems are tuned for channel fidelity, while whether the operator experiences the device as part of the body, the Sense of Embodiment (SoE), is measured only afterwards, by…TERRA: Terrain-Aware Reconstruction, Retargeting and Control for Musculoskeletal Locomotion
Recent advances in musculoskeletal modeling and reinforcement learning have enabled muscle-actuated agents to reproduce increasingly complex human motions.How much of fly walking is written in the wiring?
Connectome models of the fly nerve cord generate walking-like motor rhythms, but oscillation alone does not show that the specific wiring matters.FAST-Brain: A Flow-Aligned Spatio-Temporal Surrogate Brain Model
Modeling resting-state functional magnetic resonance imaging (rs-fMRI) data is crucial for understanding brain-wide neural activity.Separating personal from population gains when calibrating EEG foundation models for new users
Foundation models are increasingly adapted to individual users, but an apparent personalization gain can simply reflect a stronger population model.On the Limits of Metacognitive Monitoring in LLMs
Reliable decisions depend on recognizing when an answer may be wrong.NeuronDiscover: Agent-in-Twin for Mechanistic Discovery in Neuronal Microenvironments with World Action Models
Mechanistic discovery in neuronal microenvironments requires interventions and measurements that separate competing explanations of solute transport and neuronal response.NeuronSifter: Intervention Planning in CNS Microenvironments
Prioritizing central nervous system (CNS) interventions requires predicting how a dose, route, and schedule act on a partially observed microenvironment, then choosing the measurement that would…Better Behavioral Prediction, More Faithful Model Ablations? Evidence from Sequential Choice
Using predictive models to explain cognition requires more than accurate behavioral predictions.Cross-attention encoding models reveal dynamic spatiotemporal routing across human higher visual cortex
Understanding how the brain parses actions and events from time-varying natural inputs is a central challenge in neuroscience.Receptive-field-constrained stimulus optimization for human early and intermediate visual cortex
An ongoing challenge in sensory neuroscience is to characterize the feature dimensions encoded by cortical populations.Explainable Deep Learning of Resting-State Functional Connectomes Reveals Network Biomarkers of Adolescent Intelligence
Mapping resting-state brain organization to individual differences in cognitive ability remains a major challenge in population neuroinformatics.T-SNN: Temporal Simplicial Neural Network for EEG Decoding
Decoding brain states requires models that capture both the evolution of neural activity and interactions among groups of brain regions.Recovery-Directed Symbolic Distillation of Neural Likelihoods
Amortized neural likelihoods enable computationally expensive inference for models with analytically intractable or unspecified likelihoods, but their black-box nature limits interpretability.Beyond Gaussian Assumptions: Distribution-Aware Channel Capacity for Effective Connectivity
Effective-connectivity estimation from brain signals often relies on Gaussian residual modeling, which enables tractable estimation but can discard informative distributional structure and distort…FlatClip: A Geometry-Aware Surface-Level Baseline for fMRI Representation Learning
Recent fMRI foundation models differ substantially in the spatial scale at which they represent brain activity.MAESTRO: a Multimodal Auditory-attention Egocentric Speech-TRacking Open corpus
Humans rely on gaze, head movements, and visual cues to attend to speakers in noisy environments, yet auditory attention decoding (AAD) has been studied primarily using electroencephalography (EEG).A Spiking Neural Network Model of Elementary Self-Consciousness via Endogenous Default Mode Network Dynamics
Understanding the neurobiological mechanisms underlying self-referential cognition and baseline self-consciousness remains a fundamental challenge in computational neuroscience.