Neuroscience · Life Sciences
Neurons & Cognition
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163 papers, from 31 August 2026 to 5 November 2026: 140 arXiv preprints and 23 OpenAlex records.
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Cross-species representation learning aligns mouse and human neural dynamics and tracks clinical drug efficacy
Preclinical models poorly predict human drug efficacy, particularly in neurological disorders.Neural Decoding as Cognitive Inference
The brain maintains stable cognition despite continuously changing neural activity.MovieSTAGE: Scene, Transition, and Global Encoding for Movie-fMRI ADHD Classification
Naturalistic movie-fMRI provides a shared, temporally structured probe of brain dynamics, yet predictive models commonly rely on whole-run functional connectivity (FC) or temporally generic…Many Brains, One Geometry: A Shared Visual-Semantic Space for Cross-Dataset fMRI Decoding
Visual decoding from fMRI is typically siloed by participant and experiment, obscuring whether heterogeneous neural measurements can be organized within a common computational geometry.CircuitATLAS: Agentic reasoning over a systems neuroscience knowledge graph for target discovery in circuitopathies
Drug discovery for neurological disease has traditionally centered on the molecules altered by disease.Do Generative Priors Align with Human Naturalness Perception?
Visual generative models are trained to capture the probability distributions of natural images, yet whether their native priors reflect the regularities governing human perception of image…Structure alone supports efficient visual computation in the Drosophila visual system
Understanding the extent to which measured synaptic wiring determines computation remains a central challenge.Learning infinite context windows in recurrent architectures via spatial neural computing
Recurrent neural networks (RNNs) offer linear-time scaling with sequence length while requiring only constant memory, yet they struggle to capture long-range dependencies due to vanishing gradients…Similar Predictive Fit but Different Latent Dynamics: Characterizing Learned Dynamical Structure in Personalized Models of Brain Disorders
As AI models move toward clinical decision-making and personalized treatment, understanding \emph{what} a model learns is important beyond predictive accuracy alone.CANDLE: Cortical Null-Space Decomposition for Noninvasive Brain Source Imaging
Electrophysiological source imaging (ESI) aims to estimate cortical source activity from noninvasive electrophysiological measurements such as electroencephalogram (EEG).ReGraph: A Computational Account of Emergent Generalization in the "what" and "where" Dual Visual Streams
Where generalization capacity--the ability to extract context-invariant relational structures--first emerges remains a central question in AI and neuroscience.Confidence-Ordering Reversal under Contextual Priors in Neural Decoding
Contextual priors improve neural-to-language decoding by reshaping candidate scores.From the Drosophila Visual Connectome to General-Purpose Computer Vision
Biological connectomes encode structured solutions to visual computation that may provide reusable inductive biases for artificial vision.Language-model ratings of depression reflect the rater more than the patient
Depression has no diagnostic blood test.A Connectome Test of the Fly Hashing Algorithm
Dasgupta, Stevens and Navlakha (2017) showed that the Drosophila olfactory circuit, modelled as a random sparse projection followed by winner-take-all, is a locality-sensitive hash that beats…CoHyFuse: Condition-wise Hypergraph Fusion with Global Connectome in Task-fMRI
Task-fMRI connectomes reveal state-dependent neural reconfigurations, yet conventional methods marginalize these signals by aggregating distinct conditions into static pairwise graphs, thereby…From communication to computation in neurons-on-a-chip: an in silico study of neurotopomorphic computing
Living neuronal networks transform inputs through recurrent cellular and population dynamics, yet it is unknown which network architecture supports which computation.NeuroCBIR: A Fast and Accurate Image Retrieval System for Whole-Brain and Region-Specific MRI
Content-based image retrieval (CBIR) in neuroimaging enables the identification of structurally similar brain scans, supporting diagnosis, prognosis, and treatment planning; however, existing…COMPASS 2.0: psychometric representational similarity analysis distinguishes symptom structure from personal signal
Language models can score psychiatric questionnaires from speech, but agreement with self-report may reflect the questionnaire rather than the person.Lightweight Semantic EEG Foundation Model for Frozen Cross-Disorder Transfer
Large-scale EEG foundation models have demonstrated promising transferability across neurological disorders, but often require millions of parameters and substantial computational resources.