decoding

Hidden Brain State-Based Internal Evaluation Using Kernel Inverse Reinforcement Learning in Brain-Machine Interfaces
Hidden Brain State-Based Internal Evaluation Using Kernel Inverse Reinforcement Learning in Brain-Machine Interfaces 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Reinforcement learning (RL)-based brain machine interfaces (BMIs) assist paralyzed people in controlling neural prostheses without the need for real limb movement as supervised signals. The design of reward signal significantly… read more

A Wearable Brain-Computer Interface With Fewer EEG Channels for Online Motor Imagery Detection
A Wearable Brain-Computer Interface With Fewer EEG Channels for Online Motor Imagery Detection 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Motor imagery-based brain-computer interfaces (MI-BCIs) have significant potential for neurorehabilitation and motor recovery. However, most BCI systems employ multi-channel electroencephalogram (EEG) recording devices, during which the pre-experimental preparation and post-experimental… read more

FACT-Net: A Frequency Adapter CNN With Temporal-Periodicity Inception for Fast and Accurate MI-EEG Decoding
FACT-Net: A Frequency Adapter CNN With Temporal-Periodicity Inception for Fast and Accurate MI-EEG Decoding 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
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,… read more
Decoding a Cognitive Performance State from Behavioral Data in the Presence of Auditory Stimuli

Decoding a Cognitive Performance State from Behavioral Data in the Presence of Auditory Stimuli
Decoding a Cognitive Performance State from Behavioral Data in the Presence of Auditory Stimuli 789 444 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Objective: Cognitive performance state is an unobserved state that refers to the overall performance of cognitive functions. Deriving an informative observation vector as well as the adaptive model and decoder… read more

Reconstructing Multi-Stroke Characters from Brain Signals toward Generalizable Handwriting Brain-Computer Interfaces
Reconstructing Multi-Stroke Characters from Brain Signals toward Generalizable Handwriting Brain-Computer Interfaces 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Handwriting Brain-Computer Interfaces (BCIs) provides a promising communication avenue for individuals with paralysis. While English-based handwriting BCIs have achieved rapid typewriting with 26 lowercase letters (mostly containing one stroke each),… read more

USCT-UNet: Rethinking the Semantic Gap in U-Net Network From U-Shaped Skip Connections With Multichannel Fusion Transformer
USCT-UNet: Rethinking the Semantic Gap in U-Net Network From U-Shaped Skip Connections With Multichannel Fusion Transformer 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Medical image segmentation is a crucial component of computer-aided clinical diagnosis, with state-of-the-art models often being variants of U-Net. Despite their success, these models’ skip connections introduce an unnecessary semantic… read more

Cortical ROI Importance Improves MI Decoding From EEG Using Fused Light Neural Network
Cortical ROI Importance Improves MI Decoding From EEG Using Fused Light Neural Network 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Decoding motor imagery (MI) using deep learning in cortical level has potential in brain computer interface based intelligent rehabilitation. However, a mass of dipoles is inconvenient to extract the personalized… read more

Brain Network Evaluation by Functional-Guided Effective Connectivity Reinforcement Learning Method Indicates Therapeutic Effect for Tinnitus
Brain Network Evaluation by Functional-Guided Effective Connectivity Reinforcement Learning Method Indicates Therapeutic Effect for Tinnitus 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Using functional connectivity (FC) or effective connectivity (EC) alone cannot effectively delineate brain networks based on functional magnetic resonance imaging (fMRI) data, limiting the understanding of the mechanism of tinnitus… read more

Deep Pinsker and James-Stein Neural Networks for Decoding Motor Intentions from Limited Data
Author(s)3: Marko Angjelichinoski, Mohammadreza Soltani, John Choi, Bijan Pesaran, Vahid Tarokh
Deep Pinsker and James-Stein Neural Networks for Decoding Motor Intentions from Limited Data 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

Non-parametric regression has been shown to be useful in extracting relevant features from Local Field Potential (LFP) signals for decoding motor intentions. Yet, in many instances, brain-computer interfaces (BCIs) rely…

read more
Mining Within-Trial Oscillatory Brain Dynamics to Address the Variability of Optimized Spatial Filters

Mining Within-Trial Oscillatory Brain Dynamics to Address the Variability of Optimized Spatial Filters
Author(s)3: Andreas Meinel, Henrich Kolkhorst, Michael Tangermann
Mining Within-Trial Oscillatory Brain Dynamics to Address the Variability of Optimized Spatial Filters 780 435 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

   Data-driven spatial filtering algorithms optimize scores, such as the contrast between two conditions to extract oscillatory brain signal components. Most machine learning approaches for the filter estimation, however, disregard…

read more
Search this website