Results 131 to 140 of about 2,367,946 (319)
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
An AI‐Enabled All‐In‐One Visual, Proximity, and Tactile Perception Multimodal Sensor
Advanced Robotics Research, EarlyView.Targeting integrated multimodal perception of robots, an AI‐enabled all‐in‐one multimodal sensor is proposed. This sensor is capable of perceiving three types of modalities, including vision, proximity, and tactility. By toggling an ultraviolet light and adjusting the camera focus, it switches smoothly between multiple perceptual modalities, enabling ...
Menghao Pu +7 more
wiley +1 more source
Advanced Robotics Research, EarlyView.Visual teach‐and‐repeat (VTR) navigation allows robots to learn and follow routes without building a full metric map. We show that navigation accuracy for VTR can be improved by integrating a topological map with error‐drift correction based on stereo vision.
Fuhai Ling, Ze Huang, Tony J. Prescott
wiley +1 more source
Neural Manifolds in Brain-Machine Interfaces: Evaluating Their Potential for Decoding Motor Imagery [PDF]
embargoed_20280330Brain-computer interfaces (BCIs) constitute an emerging technology with significant potential to enhance communication and control for individuals with severe motor impairments.
VIRGOLINI, FRANCESCA
core
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
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
Advanced Robotics Research, EarlyView.Automated poultry processing lines still rely on humans to lift slippery, easily bruised carcasses onto a shackle conveyor. Deformability, anatomical variance, and hygiene rules make conventional suction and scripted motions unreliable. We present ChicGrasp, an end‐to‐end hardware‐software co‐designed imitation learning framework, to offer a ...
Amirreza Davar +8 more
wiley +1 more source
Neural decoding in pre-exposed and control conditions. [PDF]
, 2019 (A) Neural decoding accuracies were analyzed across time points along the stimulus duration and stimulus presentations in pre-exposed and control conditions.
David S. Vicario (7326128) +1 more
core +1 more source
Muscle Control of an Extra Robotic Digit
Advanced Robotics Research, EarlyView.This study compares muscle‐ and movement‐based control for operating a supernumerary robotic thumb. While movement control performs better in the proposed tasks, muscle‐based (EMG) control promotes broader motor learning. The results highlight the promise and challenges of using biosignals for human augmentation, offering new insights into intuitive ...
Julien Russ +7 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