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
Invariance before structure: two modes of emergent compression in representation learning
Learned representations show striking invariance across biological and artificial neural networks, with different substrates and variations driven by drift, heterogeneity and initialisation.Reversible Dynamics, Asymmetric Actions: Parking as a Trajectory-Level Affordance
Drivers are often told to back into a tight parking space, not drive in nose first.Do sEMG Foundation Models Improve Cross-Subject Generalisation?
sEMG Foundation Models aim to learn general purpose representations over diverse subjects and recording conditions that boost performance on a variety of downstream tasks.Same Behavior, Different Mechanism: What Finite Experiments Can Certify About Integrated Information
Interpretability, AI auditing and assessments of machine consciousness increasingly rest on mechanism-level quantities: functionals of a system's causal transition law that describe how it computes…Mind Control of LLMs via Closed-Loop Stimulation: Out-of-Distribution Robustness
Brains and large language models need not be considered equivalent systems to reveal an interpretable commonality: both exhibit high-dimensional, nonlinear dynamics whose behavior can only be…Time-Division Multiplexing: The Operational Rhythm and Temporal Organization Layer of Digital Life
Continual agents must handle urgent interaction while retaining alternatives, replaying errors, and committing safe long-term changes.PINR-ESI: Physics-Informed Self-Supervised Implicit Neural Representation Framework for EEG Extended-Source Imaging
EEG extended-source imaging aims to localize active cortical regions and characterize their spatial extent, yet supervised inverse networks typically depend on synthetic EEG-source pairs and may be…Learning Time-Varying Connectomes for Stable Behavior Across Development
Neural circuits must maintain functionality to drive effective behavior while their size, topology, geometry, and intrinsic dynamics change across development.Curriculum unlearning in humans and neural networks
During learning, humans often benefit from curricula that teach simple rules before exceptions.Prior Action Control Causally Alters Language-Model Plasticity
Two copies of one language model start from identical weights and receive the same rewards during training.AVID: A 5T fMRI Dataset for Benchmarking Auditory-induced Visual Mental Imagery Decoding
Visual mental imagery (VMI) decoding uses brain activity to reconstruct internally generated visual scenes, providing a potential pathway for externalizing internal experiences and developing…When Model Complexity Matters in Cross-Subject Naturalistic fMRI Prediction
Increasingly complex neural models predict blood-oxygen-level-dependent (BOLD) responses to naturalistic stimuli, but the predictive value of this added complexity remains unclear.The (Butter)fly Dream: Linear Separability of World-Model Rollouts in a Connectome-Constrained Visual Model
Zhuangzi dreamt he was a butterfly and, on waking, could not tell which was the dream.Do agents need to sleep?
LLM-based agents, which increasingly operate persistently across sessions and accumulate memory through interaction, already exhibit the familiar symptoms of unchecked plasticity: semantic drift…Modeling Visual Cortex with Layerwise Multiscale Manifold Capacity Maximization
Task-optimized deep neural networks have risen to prominence as the most predictive phenomenological models of responses in primate visual cortex, but leave much to be desired from the perspective…Adversarial robustness does not entail human-aligned categorization
Adversarial training can improve some forms of correspondence between artificial and biological vision, but whether robust classifiers acquire human-aligned classification behavior remains unclear.S1CogBench: What System One Decision Models Can and Cannot Do on Cognitive Experiments
Language models are no longer used only to generate text.From Connection Loss to Collision: Closed-Loop Fault Assessment of a Fly-Connectome SNN
The public release of the complete adult fruit-fly brain connectome enables brain-scale spiking-network studies, motivating closed-loop assessment of connection loss.Geometric and algebraic inference in humans and neural networks
Humans possess a remarkable ability to draw inferences from limited data.Latent Prediction Yields Cross-Subject Alignable Representations in Sensory-Evoked fMRI
Decoding sensory-evoked functional magnetic resonance imaging (fMRI) data is a central analytical tool in cognitive neuroscience.