Results 21 to 30 of about 19,170,582 (248)

High-Performance Cross-Subject Decoding of Multiclass Rhythmic Motor Imagery Using EEG Data From 100 Subjects

IEEE Transactions on Neural Systems and Rehabilitation Engineering
Objective: Effective cross-subject decoding is essential for reducing calibration time and enhancing the practical usability of brain-computer interfaces (BCIs).
Yuxuan Wei, Ximing Mai, Yang Li, Ruijie Luo, Ruijia Cheng, Jianjun Meng   +5 more
doaj   +1 more source

Decoding Digital Visual Stimulation From Neural Manifold With Fuzzy Leaning on Cortical Oscillatory Dynamics

Frontiers in Computational Neuroscience, 2022
A crucial point in neuroscience is how to correctly decode cognitive information from brain dynamics for motion control and neural rehabilitation.
Haitao Yu, Quanfa Zhao, Shanshan Li, Kai Li, Chen Liu, Jiang Wang   +5 more
doaj   +1 more source

A Low-Cost Modular Multi-Region Electrode for Distributed Network Recording and Brain State Decoding

Brain Sciences
Background: Precise decoding of brain states is essential for closed-loop neuromodulation, but current electrodes and recording strategies are inadequate.
Bo-Yu Wang, Yu Chen, Bin Wang, Wen Xie, Jia-Yi Zeng, Yi-Zheng Wang, Chun-Kui Zhang   +6 more
doaj   +1 more source

Decoding accuracy results.

, 2022
(A) Full model (i.e., all channels and time windows) decoding accuracy of vocal versus nonvocal for each patient. Dark and light blue bars correspond to NatS results with speech stimuli included or excluded, respectively (e.g., light blue is nonspeech ...
Avniel Ghuman (13170091), Jasmine L. Hect (10713552), Madison Remick (13170088), Taylor J. Abel (10713555), Kyle Rupp (13170085), Bharath Chandrasekaran (308320), Lori L. Holt (5349005)   +6 more
core   +1 more source

Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif, Diane Demailly, Gabriella A. Horvàth, Juan Dario Ortigoza Escobar, Nathalie Dorison, Mayté Castro Jiménez, Cécile A. Hubsch, Thomas Wirth, Gun‐Marie Hariz, Sophie Huby, Morgan Dornadic, Zohra Souei, Muhammad Mushhood Ur Rehman, Simone Hemm, Mehdi Boulaymen, Eduardo M. Moraud, Jocelyne Bloch, Xavier Vasques   +17 more
wiley   +1 more source

FACT-Net: A Frequency Adapter CNN With Temporal-Periodicity Inception for Fast and Accurate MI-EEG Decoding

IEEE Transactions on Neural Systems and Rehabilitation Engineering
Motor imagery brain-computer interface (MI-BCI) based on non-invasive electroencephalogram (EEG) signals is a typical paradigm of BCI. However, existing decoding methods face significant challenges in terms of signal decoding accuracy, real-time ...
Sixiong Ke, Banghua Yang, Yiyang Qin, Fenqi Rong, Jiayang Zhang, Yanyan Zheng   +5 more
doaj   +1 more source

Graph-Based Codes and Iterative Decoding [PDF]

, 2003
The field of error correcting codes was revolutionized by the introduction of turbo codes in 1993. These codes demonstrated dramatic performance improvements over any previously known codes, with significantly lower complexity.
Khandekar, Aamod Dinkar
core   +1 more source

Decoding accuracy for RNNs.

, 2022
a) A decoder is trained to predict the sample label from RNN neural trajectories, for the fixed-synapse RNNs. a1) The accuracy of the trained decoder as a function of time from sample onset for FS-tanh. a2) The same plot as (a1), for FS-relu.
Leo Kozachkov (9221335), Mikael Lundqvist (247816), John Tauber (14305260), Earl K. Miller (6053633), Scott L. Brincat (9199713), Jean-Jacques Slotine (133527)   +5 more
core   +1 more source

Integrated PANoptosis Profiling Identifies Immunosuppressive Subtypes and a Prognostic Signature With Functional Validation of MLKL in Glioblastoma

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective The prognosis of glioblastoma (GBM) remains highly unfavorable, largely due to high tumor heterogeneity and an immunosuppressive microenvironment. However, the functional role of PANoptosis in this context is poorly understood. Methods Patients were stratified via K‐means clustering. A risk score model was constructed using prognosis‐
Langfei Tian, Minghui Zhao, Yuanbo Hu, Kaiyue Wang, Haiguang Liu, Zetong Bai, Kebin Zheng   +6 more
wiley   +1 more source

Tensor-Network Decoding Beyond 2D

PRX Quantum
Decoding algorithms based on approximate tensor-network (TN) contraction have proven tremendously successful in decoding two-dimensional (2D) local quantum codes such as toric or surface codes and color codes, effectively achieving optimal decoding ...
Christophe Piveteau, Christopher T. Chubb, Joseph M. Renes   +2 more
doaj   +1 more source