Results 101 to 110 of about 46,112 (290)
Using data from cue presentations results in grossly overestimating semantic BCI performance
Scientific ReportsNeuroimaging studies have reported the possibility of semantic neural decoding to identify specific semantic concepts from neural activity. This offers promise for brain-computer interfaces (BCIs) for communication.
Milan Rybář, Riccardo Poli, Ian Daly
doaj +1 more source
eLife, 2014 Trial by trial covariations between neural activity and perceptual decisions (quantified by choice Probability, CP) have been used to probe the contribution of sensory neurons to perceptual decisions.
Yong Gu +2 more
doaj +1 more source
Data‐Efficient Electromagnetic Surrogate Solver Through Dissipative Relaxation Transfer Learning
Advanced Optical Materials, EarlyView.Dissipative relaxation transfer learning (DIRTL) enables data‐efficient training of electromagnetic surrogate solvers by pretraining data generated with artificial material loss before fine‐tuning on target lossless data. The framework suppresses resonant outlier effects during early training, allowing effective adaptation to high‐amplitude resonances ...
Sunghyun Nam +2 more
wiley +1 more source
Finger movement inference using M1 neural activities
Journal of Measurement Science and Instrumentation, 2012 The paper presents the neural decoding result of finger or wrist movements using the primary motor cortex（M1）neural activities prior to its movement.It is well known that the observations of motor commands in brain are in advance before motor movements ...
Jonghoon Yoon +4 more
doaj
Stable Imitation of Multigait and Bipedal Motions for Quadrupedal Robots Over Uneven Terrains
Advanced Robotics Research, EarlyView.How are quadrupedal robots empowered to execute complex navigation tasks, including multigait and bipedal motions? Challenges in stability and real‐world adaptation persist, especially with uneven terrains and disturbances. This article presents an imitation learning framework that enhances adaptability and robustness by incorporating long short‐term ...
Erdong Xiao +3 more
wiley +1 more source
Brain Encoding and Decoding in fMRI with Bidirectional Deep Generative Models
Engineering, 2019 Brain encoding and decoding via functional magnetic resonance imaging (fMRI) are two important aspects of visual perception neuroscience. Although previous researchers have made significant advances in brain encoding and decoding models, existing methods
Changde Du +3 more
doaj +1 more source
Quality-Aware Decoding for Neural Machine Translation
, 2022 This research paper proposes quality-aware decoding for neural machine translation (NMT), which leverages recent advances in MT quality evaluation to generate better translations.
Graham Neubig +7 more
core +1 more source
Information Transmission Strategies for Self‐Organized Robotic Aggregation
Advanced Robotics Research, EarlyView.In this review, we discuss how information transmission influences the neighbor‐based self‐organized aggregation of swarm robots. We focus specifically on local interactions regarding information transfer and categorize previous studies based on the functions of the information exchanged.
Shu Leng +5 more
wiley +1 more source
Advanced Robotics Research, EarlyView.An introduction for multidrive and environment‐adaptive micro/nanorobotics: design and fabrication strategies, intelligent actuation, and their applications. Various intelligent actuation approaches—magnetic, acoustic, optical, chemical, and biological—can be synergistically designed to enhance flexibility and adaptive behavior for precision medicine ...
Aiqing Ma +10 more
wiley +1 more source
Inferential Pitfalls in Decoding Neural Representations [PDF]
, 2017 A key challenge for cognitive neuroscience is to decipher the representational schemes of the brain. A recent class of decoding algorithms for fMRI data, stimulus-feature-based encoding models, is becoming increasingly popular for inferring the ...
Caitlin Tenison +8 more
core +1 more source