Results 11 to 20 of about 634 (170)
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 +5 more
doaj +1 more source
A Low-Cost Modular Multi-Region Electrode for Distributed Network Recording and Brain State Decoding
Brain SciencesBackground: Precise decoding of brain states is essential for closed-loop neuromodulation, but current electrodes and recording strategies are inadequate.
Bo-Yu Wang +6 more
doaj +1 more source
Identification of the plant mitochondrial OrfX protein: A mass spectrometry approach
FEBS Letters, EarlyView.The mitochondrial genome of plants contains an open reading frame, orfx, which encodes a rare protein that has so far escaped mass spectrometric detection. The protein resembles the c‐subunit of bacterial twin‐arginine‐motif‐dependent protein translocases (TatC).
Matthias Döring +3 more
wiley +1 more source
IEEE Transactions on Neural Systems and Rehabilitation EngineeringMotor 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 +5 more
doaj +1 more source
Epilepsy‐Associated Variants of a Single SCN1A Codon Exhibit Divergent Functional Properties
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Pathogenic variants in SCN1A, which encodes the voltage‐gated sodium channel NaV1.1, are associated with multiple epilepsy syndromes exhibiting a range of clinical severity. SCN1A variants are reported in different syndromes, including Dravet syndrome, which is associated with loss‐of‐function, whereas neonatal/infantile‐onset ...
Lanie N. Liebovitz +3 more
wiley +1 more source
Tensor-Network Decoding Beyond 2D
PRX QuantumDecoding 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 +2 more
doaj +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 +17 more
wiley +1 more source
Cognitive computing method based on decoding psychological emotional states
International Journal of Cognitive Computing in EngineeringThe current artificial intelligence is constrained to passively executing human command control. It cannot perceive, learn, and guide itself. Furthermore, the majority of these systems are unable to comprehend the human psychological cognitive state or ...
Baihui Huangfu, Wenjuan Cheng
doaj +1 more source
Frontiers in Neuroscience, 2022 ObjectiveMulti-frequency steady-state visual evoked potential (SSVEP) stimulation and decoding methods enable the representation of a large number of visual targets in brain-computer interfaces (BCIs).
Jing Mu +6 more
doaj +1 more source
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 +6 more
wiley +1 more source