Výsledky vyhledávání - "Decoding"

Decoding subject-driven cognitive states with whole-brain connectivity patterns Autor Shirer, W R, Ryali, S, Rykhlevskaia, E, Menon, V, Greicius, M D

“… To date, methods for decoding more continuous and purely subject-driven cognitive states have not been…”
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MindBridge: A Cross-Subject Brain Decoding Framework Autor Wang, Shizun, Liu, Songhua, Tan, Zhenxiong, Wang, Xinchao

“…). Currently, brain decoding is confined to a per-subject-per-model paradigm, limiting its applicability to the same individual for whom the decoding model is trained…”
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Synchronization of Complex Dynamical Networks Subject to DoS Attacks: An Improved Coding-Decoding Protocol Autor Xing, Mengping, Lu, Jianquan, Qiu, Jianlong, Shen, Hao

“…This article investigates the synchronization of communication-constrained complex dynamic networks subject to malicious attacks…”
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An empirical evaluation of functional alignment using inter-subject decoding Autor Bazeille, Thomas, DuPre, Elizabeth, Richard, Hugo, Poline, Jean-Baptiste, Thirion, Bertrand

“…•Methods that improve inter-subject decoding accuracy reduce inter-individual variability without losing signal specificity…”
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Adaptive deep feature representation learning for cross-subject EEG decoding Autor Liang, Shuang, Li, Linzhe, Zu, Wei, Feng, Wei, Hang, Wenlong

“… the development of decoding models with strong generalizability, particularly when the available data is limited…”
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A temporal–spectral fusion transformer with subject-specific adapter for enhancing RSVP-BCI decoding Autor Li, Xujin, Wei, Wei, Qiu, Shuang, He, Huiguang

“… The performance improvement of traditional decoding methods relies on a substantial amount of training data from new test subjects, which increases preparation time for BCI systems…”
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Decoding Movement-Related Cortical Potentials Based on Subject-Dependent and Section-Wise Spectral Filtering Autor Jeong, Ji-Hoon, Kwak, No-Sang, Guan, Cuntai, Lee, Seong-Whan

“… (BMI) is an accurate decoding of the user intention for real-world environments. However, the performance remains insufficient for real-time decoding owing to the endogenous signal characteristics compared to other BMI paradigms…”
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Learning joint space–time–frequency features for EEG decoding on small labeled data Autor Zhao, Dongye, Tang, Fengzhen, Si, Bailu, Feng, Xisheng

“… Most existing EEG decoding methods separate feature extraction from classification and thus are not robust across different BCI users…”
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Low-Dimensional Subject Representation-Based Transfer Learning in EEG Decoding Autor Jeng, Po-Yuan, Wei, Chun-Shu, Jung, Tzyy-Ping, Wang, Li-Chun

“… This study presents a transfer-learning framework for EEG decoding based on the low-dimensional representations of subjects learned from the pre-trial EEG…”
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Group‐level brain decoding with deep learning Autor Csaky, Richard, van Es, Mats W. J., Jones, Oiwi Parker, Woolrich, Mark

“… Decoding is typically subject‐specific and does not generalise well over subjects, due to high amounts of between subject variability…”
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Subject-adaptive SSVEP decoding based on time–frequency information Autor Fan, Mingyang, Sang, Zhenhua, Wu, Jian, Guo, Yuzhu

“… Supervised methods such as Task Related Component Analysis (TRCA), on the other hand, perform well in short time windows but exhibit weak under cross-subject generalization…”
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Deep Transfer Learning in Intra-subject and Inter-subjects for Intracortical Brain Machine Interface Decoding Autor Fu, Zhongzheng, Zhang, Peng, He, Xinrun, Wang, Haoyuan, Guo, Yifei, Chen, Xingjian, Huang, Jian

“…Objective: This study proposes an Improved Deep Transfer Network (IDTN) to enhance decoding accuracy, calibration efficiency, and adaptability of intracortical brain machine interface (iBMI…”
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Frequency decoding of calcium oscillations Autor Smedler, Erik, Uhlén, Per

“…), much similar to a radio signal. The decoding of the oscillatory signal is typically performed by enzymes with multiple Ca2…”
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Decoding intervention for young students with mild intellectual disabilities: A single-subject design study Autor Fälth, Linda, Selenius, Heidi, Sand, Christina, Svensson, Idor

“…Students with intellectual disabilities need more time and explicit instruction to develop word decoding…”
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A Multi-Source Transfer Joint Matching Method for Inter-Subject Motor Imagery Decoding Autor Wei, Fulin, Xu, Xueyuan, Jia, Tianyuan, Zhang, Daoqiang, Wu, Xia

“…Individual differences among different subjects pose a great challenge to motor imagery (MI) decoding…”
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Supervised Contrastive Learning-Based Domain Generalization Network for Cross-Subject Motor Decoding Autor Zhi, Hongyi, Yu, Tianyou, Gu, Zhenghui, Lin, Zhuobin, Che, Le, Li, Yuanqing, Yu, Zhuliang

“…) decoding system that is both highly accurate and calibration-free for cross-subject applications remains challenging due to domain shift problem inherent in such scenario…”
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Cross-Dataset Variability Problem in EEG Decoding With Deep Learning Autor Xu, Lichao, Xu, Minpeng, Ke, Yufeng, An, Xingwei, Liu, Shuang, Ming, Dong

“…Cross-subject variability problems hinder practical usages of Brain-Computer Interfaces…”
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Learning a common dictionary for subject-transfer decoding with resting calibration Autor Morioka, Hiroshi, Kanemura, Atsunori, Hirayama, Jun-ichiro, Shikauchi, Manabu, Ogawa, Takeshi, Ikeda, Shigeyuki, Kawanabe, Motoaki, Ishii, Shin

“… Such variability complicates the analysis of data from multiple subjects and sessions in a consistent way, and degrades the performance of subject-transfer decoding in a brain–machine interface (BMI…”
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NEXUS: Neural cross-modal expression with subject-unified synthesis for brain–vision–language decoding Autor Jin, Xiao, Wang, Yongxiong, Huang, Shuai, Du, Yukun, Zhang, Nan

“… We propose NEXUS, a comprehensive framework that integrates subject-specific adaptations with multi-task learning for brain–vision–language decoding…”
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Causal decoding of individual cortical excitability states Autor Metsomaa, J., Belardinelli, P., Ermolova, M., Ziemann, U., Zrenner, C.

“…•Fluctuating cortical excitability state can be estimated from ongoing EEG.•Individual spatio-temporal classification filters are derived from EEG−TMS−EMG…”
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