Neural Decoding

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16 papers in the last four weeks, up 433% on the four weeks before. 0.2% of all new papers.

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Zero-Shot Imagined Speech Decoding via Imagined-to-Listened MEG Mapping
May 8, 2026Maryam Maghsoudi, Shihab ShammaBrain-Computer Interfaces Neural Decoding
University of Maryland · College Park, MD 20740
Interpreting V1 Population Activity via Image-Neural Latent Representation Alignment
May 5, 2026Xin Wang, Zhuangzhi Gao, Hongyi Qin +3Contrastive Learning Neural Processes
School of Psychological and Cognitive Sciences, Peking University, Beijing, China · Department of Primary Care and Mental Health, University of Liverpool, Liverpool, United Kingdom · Liverpool Centre for Cardiovascular Science, University of Liverpool, Liverpool, United Kingdom +2
Leveraging Code Automorphisms for Improved Syndrome-Based Neural Decoding
May 5, 2026Raphaël Le Bidan, Ahmad Ismail, Elsa Dupraz +1Neural Decoding
IMT Atlantique, Lab-STICC UMR CNRS 6285, Brest, France
Beyond Activation Alignment: The Geometry of Neural Sensitivity
May 4, 2026Amirhossein Yavari, Farnaz Zamani EsfahlaniNeural Representation Geometry Neural Decoding
Stephenson School of Biomedical Engineering, University of Oklahoma · Data Science and Analytics Institute, University of Oklahoma
StableMind: Source-Free Cross-Subject fMRI Decoding with Regularized Adaptation
May 4, 2026Jintao Guo, Lin Wang, Shumeng Li +5Source-Free Domain Adaptation Neural Decoding
National Key Laboratory for Novel Software Technology and the Institute of Brain-Machine Interface, Nanjing University, Nanjing 210023, China · School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798 · School of Intelligence Science and Technology, Nanjing University, Nanjing 215163, China +2
UniBCI: Towards a Unified Pretrained Model for Invasive Brain-Computer Interfaces
Apr 30, 2026Binjie Hong, Rui Xiong, Liyuan Han +1Brain-Computer Interfaces Self-Supervised Pre-Training
Brain Science Data Center · CEBSIT, Institute of Neuroscience
Inverting Foundation Models of Brain Function with Simulation-Based Inference
Apr 26, 2026Niels Bracher, Xavier Intes, Stefan T. RadevNeural Decoding
Center for Modeling, Simulation, & Imaging in Medicine, Rensselaer Polytechnic Institute, NY, USA.
EyeBrain: Left and Right Brain Lateralization Activity Classification Through Pupil Diameter and Fixation Duration
Apr 26, 2026Ko Watanabe, Pooja Pol, Nicolas Großmann +2Neural Decoding Eye Tracking
RPTU Kaiserslautern-Landau & DFKI GmbH, Germany · DFKI GmbH, Germany · RPTU Kaiserslautern-Landau, Germany +1
NAKUL-Med: Spectral-Graph State Space Models with Dynamics Kernels for Medical Signals
Apr 24, 2026Badri N. Patro, Vijay S. AgneeswaranElectroencephalography Neural Decoding
Microsoft
Decoding High-Dimensional Finger Motion from EMG Using Riemannian Features and RNNs
Apr 24, 2026Martin Colot, Cédric Simar, Guy Cheron +23D Hand Pose Estimation Neural Decoding
Machine Learning Group, ULB, Bruxelles, Belgium · § These authors contributed equally to this work and share ﬁrst authorship. · Neuromove, ULB Neuroscience Institute, ULB, Brussels, Belgium +1
Leakage-Audited Benchmarking Reveals Limited Evidence for Cross-Subject Auditory-Evoked EEG Vowel Perception Decoding
Apr 22, 2026Xiaoyang Li, Zeyan TaoCross-Subject EEG Decoding Electroencephalography
College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110016, China
MoDAl: Self-Supervised Neural Modality Discovery via Decorrelation for Speech Neuroprosthesis
Apr 22, 2026Yuanhao Chen, Peter ChinBrain-Computer Interfaces Neural Decoding
Dartmouth College Hanover, NH, USA
OmniMouse: Scaling properties of multi-modal, multi-task Brain Models on 150B Neural Tokens
Apr 20, 2026Konstantin F. Willeke, Polina Turishcheva, Alex Gilbert +18Neural Decoding Visual Neuroscience
Department of Ophthalmology, Byers Eye Institute, Stanford University · 2Stanford Bio-X, Stanford University · 3Wu Tsai Neurosciences Institute, Stanford University +6
Seeing the imagined: latent functional alignment in visual imagery decoding from fMRI data
Apr 15, 2026Fabrizio Spera, Tommaso Boccato, Michal Olak +2Neural Decoding Visual Neuroscience
Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy · Tether Evo · A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, USA
SHINE: Sequential Hierarchical Integration Network for EEG and MEG
Feb 27, 2026Xiran Xu, Yujie Yan, Songyi Li +4Electroencephalography Neural Processes
Speech and Hearing Research Center, School of Intelligence Science and Technology, Peking University, China · National Key Laboratory of General Artificial Intelligence, China · Center for BioMed-X Research, Academy for Advanced Interdisciplinary Studies, Peking University, China
Neural Minimum Weight Perfect Matching for Quantum Error Codes
Jan 1, 2026Yotam Peled, David Zenati, Eliya NachmaniNeural Decoding Quantum Error Correction
School of Electrical and Computer Engineering (ECE), Ben-Gurion University, Beer Sheva, Israel.
NeuroSketch: A Practical Design Recipe for Neural Decoding
Dec 10, 2025Gaorui Zhang, Zhizhang Yuan, Jialan Yang +4Brain-Computer Interfaces Neural Decoding
College of Computer Science and Technology, Zhejiang University · Shanghai Institute of Microsystem and Information Technology
Geometry-Aware Deep Congruence Networks for Manifold Learning in Cross-Subject Motor Imagery
Nov 24, 2025Sanjeev Manivannan, Chandra Shekar LakshminarayanCross-Subject EEG Decoding MI Classification
Department of Biotechnology · Department of Data Science and Artificial Intelligence
Hi-DREAM: Brain-Inspired Hierarchical Diffusion for fMRI-to-Image Reconstruction via ROI Encoder and VisuAl Mapping
Nov 14, 2025Guowei Zhang, Yun Zhao, Kai Sun +4Neural Decoding Conditional Image Generation
Dept of Data Science and AI, Monash University, Melbourne, Australia · Brain and Mind Centre, University of Sydney, Sydney, Australia · School of Psychological Sciences, Monash University, Melbourne, Australia
Qubit-centric Transformer for Surface Code Decoding
Oct 13, 2025Seong-Joon Park, Hee-Youl Kwak, Yongjune KimNeural Decoding Quantum Error Correction
Samsung Electronics Company, Ltd., Suwon 16677, South Korea · Institute of Artificial Intelligence, Pohang University of Science and Technology (POSTECH), Pohang 37673, South Korea · Department of Electrical, Electronic and Computer Engineering, University of Ulsan, Ulsan 44610, South Korea +1
Robust Sparse Bayesian Learning Based on Minimum Error Entropy for Noisy High-Dimensional Brain Activity Decoding
Aug 5, 2025Yuanhao Li, Badong Chen, Wenjun Bai +2Neural Decoding Bayesian Inference
Center for Advanced Intelligence Project, RIKEN, Tokyo 103-0027, Japan · Department of Computational Brain Imaging, ATR Neural Information Analysis Laboratories, Kyoto 619-0237, Japan · Institute of Artificial Intelligence and Robotics (IAIR), Xi’an Jiaotong University, Xi’an 710049, China +1
A Multimodal Sequence-to-Sequence Model for Cross-Subject Prediction of Brain Responses to Naturalistic Stimuli
Jul 24, 2025Qianyi He, Monica D. Rosenberg, Yuan Chang LeongNeural Decoding Neuroimaging
Data Science Institute University of Chicago, USA · Department of Psychology, Neuroscience Institute University of Chicago, USA
Decoding the Multimodal Mind: Generalizable Brain-to-Text Translation via Multimodal Alignment and Adaptive Routing
May 15, 2025Chunyu Ye, Yunhao Zhang, Jingyuan Sun +3Brain-Computer Interfaces Neural Decoding
1State Key Laboratory of Multimodal Artificial Intelligence System, Institute of Automation, Chinese Academy of Sciences · School of Artificial Intelligence, University of Chinese Academy of Sciences · Department of Computer Science, The University of Manchester +1
Machine Learning-Based Classification of Jhana Advanced Concentrative Absorption Meditation Using 7 Tesla Functional Magnetic Resonance Imaging
Date pendingPuneet Kumar, Winson F. Z. Yang, Alakhsimar Singh +2Neural Decoding Neuroimaging
School of AI and Data Engineering, Indian Institute of Technology Ropar 140001, India · Meditation Research Program, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA · Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA +2

May 8, 2026, cs.LGJ/K move · Enter open · S save

Zero-Shot Imagined Speech Decoding via Imagined-to-Listened MEG Mapping

Maryam Maghsoudi, Shihab Shamma

University of Maryland · College Park, MD 20740

Brain-Computer Interfaces Neural Decoding Neuroimaging

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Decoding imagined speech from non-invasive brain recordings is challenging because imagined datasets are scarce and difficult to align temporally across subjects and sessions In this work, we propose a new approach to the decoding of imagined speech that leverages the richer and more reliably labeled recordings during listening to speech. We collected paired listened and imagined MEG recordings to rhythmic melodic and spoken stimuli from trained musicians. Using trained musicians helped improve temporal alignment across conditions. We then developed a three-stage decoding pipeline that revealed consistent and meaningful relationships between neural activity evoked by imagining and listening to the same stimuli. First, we trained six linear and neural models to map imagined MEG responses to listened responses. We evaluated these models against a null baseline from unseen subjects to validate that the predicted-listening responses preserve stimulus-specific information. In the second stage, we trained a contrastive word decoder exclusively on the listened MEG responses, and evaluated it using four embedding strategies including semantic, acoustic, and phonetic representations. In the third stage, we process the imagined MEG responses from held-out subjects through the mapping pipeline to compute the corresponding listening responses that are then decoded by the listened decoder. Using rank-based analysis, we show that the imagined words are decodable significantly above chance. We shall report here the results of a proof-of-concept implementation to decode imagined speech, where all evaluations are performed on held-out subjects. We also demonstrate that performance improves with training data size, suggesting that this approach is scalable and can directly be made applicable to realistic brain-computer interface scenarios.

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Latest papers 114