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๐Ÿ” models ๐Ÿ“‚ Neuroscience
Showing 4287 results for "models" in Neuroscience
Neuroscience Preprint PDF DOI

Multisensory learning recruits visual neurons into an olfactory memory engram

Zeynep Okray, Nils Otto, Anna A. Cook, Clifford Talbot, Ashwin Miriyala, Martin Klappenbach, Ciara Stern, Kieran Desmond, Paola Vargas-Gutierrez, Scott Waddell ยท 2026

Associating multiple sensory cues with a single experience or object is a fundamental process that improves object recognition and memory performance. However, neural mechanisms that bind sensory featโ€ฆ

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Neuroscience Preprint PDF DOI

On Agentic Behavioral Modeling

Dirk Ostwald, Rasmus Bruckner, Franziska Usee, Belinda Fleischmann, Joram Soch, Sean Mulready ยท 2026

Integrating theoretical neuroscience, decision theory, and probabilistic inference offers a promising route to understanding human cognition, yet concrete methodological bridges between agentic AI modโ€ฆ

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Neuroscience Preprint PDF DOI

A geometry aware framework enhances noninvasive mapping of whole human brain dynamics

Song Wang, Kexin Lou, Chen Wei, Zhiyuan Sheng, Jiahao Tang, Kaining Peng, Xinke Shen, Shuhao Mei, Liang Chen, Dongfeng Gu, Quanying Liu ยท 2026

Non-invasive electrophysiology lacks methods that accurately reconstruct whole-brain spatiotemporal dynamics while incorporating individual cortical geometry, leaving current electroencephalography anโ€ฆ

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Neuroscience Preprint PDF DOI

One-shot emergency psychiatric triage across 15 frontier AI chatbots

Veith Weilnhammer, Lennart Luettgau, Christopher Summerfield, Viknesh Sounderajah, Elise Wilkinson, Virginia Corno, Matthew M Nour ยท 2026

AI chatbots are increasingly used for health advice, but their performance in psychiatric triage remains undercharacterized. Psychiatric triage is particularly challenging because urgency must often bโ€ฆ

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Neuroscience Preprint PDF DOI

The Genetic and Environmental Architecture of the Human Functional Connectome

Tanu Raghav, Daniel Guerrero, Uttara Tipnis, Julie Sara Benny, Mintao Liu, Mario Dzemidzic, Arian Ashourvan, Alex P. Miller, Beau Ances, Jaroslaw Harezlak, Joaquin Goni ยท 2026

Functional connectivity varies across individuals due to genetic and environmental factors, yet classical twin models typically confound non-shared environment with measurement error and are largely lโ€ฆ

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Neuroscience Preprint PDF DOI

Integrative neurocybernetic modeling in the era of large-scale neuroscience

Il Memming Park, Ayesha Vermani, Gonzalo G. de Polavieja, Juan Alvaro Gallego, Kathleen Esfahany, Shreya Saxena, Michael Orger, Auke Ijspeert, Matthew Dowling, Daniel McNamee, Srinivas C. Turaga, Zachary Mainen, Joseph J. Paton, Alfonso Renart ยท 2026

Large-scale neuroscience is generating rich datasets across animals, brain areas and behavioral contexts, yet our modeling efforts remains fragmented across isolated experiments. We argue that understโ€ฆ

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Triple Configuration of Brain Networks Based on Recurrent Neural Networks: The Synergistic Effects of Exogenous Stimuli, Task Demands, and Spontaneous Activity

Binghao Yang, Guangzong Chen ยท 2026

The foundation of cognitive flexibility and higher-order intelligence lies in the functional structure and activity of brain networks, which can be dynamically configured by both external environmentsโ€ฆ

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Neuroscience Preprint PDF DOI

Foundation models for discovering robust biomarkers of neurological disorders from dynamic functional connectivity

Deepank Girish, Yi Hao Chan, Sukrit Gupta, Jing Xia, Jagath C. Rajapakse ยท 2026

Several brain foundation models (FM) have recently been proposed to predict brain disorders by modelling dynamic functional connectivity (FC). While they demonstrate remarkable model performance and zโ€ฆ

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Neuroscience Preprint PDF DOI

Modulating Cross-Modal Convergence with Single-Stimulus, Intra-Modal Dispersion

Eghbal A. Hosseini, Brian Cheung, Evelina Fedorenko, Alex H. Williams ยท 2026

Neural networks exhibit a remarkable degree of representational convergence across diverse architectures, training objectives, and even data modalities. This convergence is predictive of alignment witโ€ฆ

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Neuroscience Preprint PDF DOI

Only Brains Align with Brains: Cross-Region Alignment Patterns Expose Limits of Normative Models

Larissa Hofling, Matthias Tangemann, Lotta Piefke, Susanne Keller, Katrin Franke, Matthias Bethge ยท 2026

Neuroscientists and computer vision researchers use model-brain alignment benchmarks to compare artificial and biological vision systems. These benchmarks rank models according to alignment measures sโ€ฆ

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Modelling time-order effects in haptic perception with a Bayesian dynamical framework

Gaston Avetta, Jose Lobera, Juan Jose Zarate, Ines Samengo, Damian G. Hernandez ยท 2026

Perceptual judgments of sequential stimuli are systematically biased by prior expectations and by the temporal structure of sensory input. In haptic discrimination tasks, these effects often manifest โ€ฆ

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Neuroscience Preprint PDF DOI

OmniMouse: Scaling properties of multi-modal, multi-task Brain Models on 150B Neural Tokens

Konstantin F. Willeke, Polina Turishcheva, Alex Gilbert, Goirik Chakrabarty, Hasan A. Bedel, Paul G. Fahey, Yongrong Qiu, Marissa A. Weis, Michaela Vystrcilova, Taliah Muhammad, Lydia Ntanavara, Rachel E. Froebe, Kayla Ponder, Zheng Huan Tan, Emin Orhan, Erick Cobos, Sophia Sanborn, Katrin Franke, Fabian H. Sinz, Alexander S. Ecker, Andreas S. Tolias ยท 2026

Scaling data and artificial neural networks has transformed AI, driving breakthroughs in language and vision. Whether similar principles apply to modeling brain activity remains unclear. Here we leverโ€ฆ

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The Umwelt Representation Hypothesis: Rethinking Universality

Victoria Bosch, Rowan Sommers, Adrien Doerig, Tim C Kietzmann ยท 2026

Recent studies reveal striking representational alignment between artificial neural networks (ANNs) and biological brains, leading to proposals that all sufficiently capable systems converge on univerโ€ฆ

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Quantum-Like Models of Cognition and Decision Making: Open-Systems and Gorini--Kossakowski--Sudarshan--Lindblad Dynamics

Masanari Asano, Andrei Khrennikov ยท 2026

This paper starts with surveying the evolution of quantum-like models of cognition and decision making, transitioning from static kinematic representations to a robust dynamical framework based on opeโ€ฆ

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Neuroscience Preprint PDF DOI

Poisson Flow Model of Cortical Folding Pattern

Moo K. Chung, Luigi Maccotta, Aaron Struck ยท 2026

Cortical folding reflects coordinated neurodevelopmental processes and provides a sensitive marker of neurological disease. In juvenile myoclonic epilepsy (JME), structural abnormalities are subtle anโ€ฆ

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Neuroscience Preprint PDF DOI

Causality as a Minimum Energy Principle

Moo K. Chung, D. Vijay Anand, Anass B El-Yaagoubi, Jae-Hun Jung, Anqi Qiu, Hernando Ombao ยท 2026

Classical causal models, such as Granger causality and structural equation modeling, are largely restricted to acyclic interactions and struggle to represent cyclic and higher-order dynamics in compleโ€ฆ

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Neuroscience Preprint PDF DOI

Robust Evaluation of Neural Encoding Models via ground-truth approximation

Giovanni M. Di Liberto ยท 2026

Encoding models enable measurement of how our brains represent sensory inputs using electro-and magneto-encephalography (MEEG). Evaluating how closely encoding models reflect the underlying brain funcโ€ฆ

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Neuronal electricality founded in murburn-thermodynamic principles: 1. Background and basic theoretical formulation

Kelath Murali Manoj, Nagamani Sukumar ยท 2026

Trans-membrane gradients and fluxes of cations (H+, Na+, K+, etc.) were deemed to be the rationale of electrical activities of aerobic cells/organelles, as per classical perceptions. Murburn concept (โ€ฆ

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Seeing the imagined: a latent functional alignment in visual imagery decoding from fMRI data

Fabrizio Spera, Tommaso Boccato, Michal Olak, Sara Cammarota, Matteo Ciferri, Michelangelo Tronti, Nicola Toschi, Matteo Ferrante ยท 2026

Recent progress in visual brain decoding from fMRI has been enabled by large-scale datasets such as the Natural Scenes Dataset (NSD) and powerful diffusion-based generative models. While current pipelโ€ฆ

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Machine learning approaches to uncover the neural mechanisms of motivated behaviour: from ADHD to individual differences in effort and reward sensitivity

Nam Trinh ยท 2026

Motivated behaviour relies on the brain's capacity to evaluate effort and reward. Dysregulation within these processes contributes to a spectrum of conditions, from hyperactivity in attention-deficit/โ€ฆ

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