Ian Daly
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View article: Electrophysiological Correlates of the Uncanny Valley
Electrophysiological Correlates of the Uncanny Valley Open
To understand how the brain responds to robots with varying levels of human-likeness, we investigated the electrophysiological neural correlates of the uncanny valley effect while human observers viewed pictures of various robot faces. We …
View article: Effective Connectivity-Based Unsupervised Channel Selection Method for EEG
Effective Connectivity-Based Unsupervised Channel Selection Method for EEG Open
Analyzing neural data such as Electroencephalography (EEG) data often involves dealing with high-dimensional datasets, where not all channels provide equally meaningful informa- tion. Selecting the most relevant channels is crucial for imp…
View article: Electrophysiological Correlates of the Uncanny Valley
Electrophysiological Correlates of the Uncanny Valley Open
The present study investigated the electrophysiological correlates of the uncanny valley effect while human observers viewed pictures of various robot faces. We found characteristic non-linear trajectories of the N400 amplitude against the…
View article: Simultaneous EEG and fNIRS recordings for semantic decoding of imagined animals and tools
Simultaneous EEG and fNIRS recordings for semantic decoding of imagined animals and tools Open
Semantic neural decoding aims to identify which semantic concepts an individual focuses on at a given moment based on recordings of their brain activity. We investigated the feasibility of semantic neural decoding to develop a new type of …
View article: Electrophysiological Correlates of the Uncanny Valley
Electrophysiological Correlates of the Uncanny Valley Open
To understand how the brain responds to robots with varying levels of human-likeness, we investigated the electrophysiological neural correlates of the uncanny valley effect while human observers viewed pictures of various robot faces. We …
View article: Electrophysiological Correlates of the Uncanny Valley
Electrophysiological Correlates of the Uncanny Valley Open
To understand how the brain responds to robots with varying levels of human-likeness, we investigated the electrophysiological neural correlates of the uncanny valley effect while human observers viewed pictures of various robot faces. We …
View article: Electrophysiological Correlates of the Uncanny Valley
Electrophysiological Correlates of the Uncanny Valley Open
To understand how the brain responds to robots with varying levels of human-likeness, we investigated the electrophysiological neural correlates of the uncanny valley effect while human observers viewed pictures of various robot faces. We …
View article: Electrophysiological Correlates of the Uncanny Valley
Electrophysiological Correlates of the Uncanny Valley Open
To understand how the brain responds to robots with varying levels of human-likeness, we investigated the electrophysiological neural correlates of the uncanny valley effect while human observers viewed pictures of various robot faces. We …
View article: Editorial: Datasets for brain-computer interface applications, volume II
Editorial: Datasets for brain-computer interface applications, volume II Open
View article: TMS-evoked potential propagation reflects effective brain connectivity
TMS-evoked potential propagation reflects effective brain connectivity Open
Objective. Cognition is achieved through communication between brain regions. Consequently, there is considerable interest in measuring effective connectivity. A promising effective connectivity metric is transcranial magnetic stimulation …
View article: Using data from cue presentations results in grossly overestimating semantic BCI performance
Using data from cue presentations results in grossly overestimating semantic BCI performance Open
Neuroimaging 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. However, translating th…
View article: Corrigendum: Decoding of semantic categories of imagined concepts of animals and tools in fNIRS (2021 <i>J. Neural Eng.</i> 18 046035)
Corrigendum: Decoding of semantic categories of imagined concepts of animals and tools in fNIRS (2021 <i>J. Neural Eng.</i> 18 046035) Open
View article: Inter-Participant Transfer Learning with Attention Based Domain Adversarial Training for P300 Detection
Inter-Participant Transfer Learning with Attention Based Domain Adversarial Training for P300 Detection Open
View article: Editorial: Explainable and advanced intelligent processing in the brain-machine interaction
Editorial: Explainable and advanced intelligent processing in the brain-machine interaction Open
EDITORIAL article Front. Hum. Neurosci., 12 September 2023Sec. Brain-Computer Interfaces Volume 17 - 2023 | https://doi.org/10.3389/fnhum.2023.1280281
View article: Feature learning framework based on EEG graph self-attention networks for motor imagery BCI systems
Feature learning framework based on EEG graph self-attention networks for motor imagery BCI systems Open
View article: Neural decoding of music from the EEG
Neural decoding of music from the EEG Open
View article: Classification of Motor Imagery Based on Multi-Scale Feature Extraction and the Channel-Temporal Attention Module
Classification of Motor Imagery Based on Multi-Scale Feature Extraction and the Channel-Temporal Attention Module Open
Motor imagery (MI) is a popular paradigm for controlling electroencephalogram (EEG) based Brain-Computer Interface (BCI) systems. Many methods have been developed to attempt to accurately classify MI-related EEG activity. Recently, the dev…
View article: Novel channel selection model based on graph convolutional network for motor imagery
Novel channel selection model based on graph convolutional network for motor imagery Open
View article: Sonic enhancement of virtual exhibits
Sonic enhancement of virtual exhibits Open
Museums have widely embraced virtual exhibits. However, relatively little attention is paid to how sound may create a more engaging experience for audiences. To begin addressing this lacuna, we conducted an online experiment to explore how…
View article: SincNet-Based Hybrid Neural Network for Motor Imagery EEG Decoding
SincNet-Based Hybrid Neural Network for Motor Imagery EEG Decoding Open
It is difficult to identify optimal cut-off frequencies for filters used with the common spatial pattern (CSP) method in motor imagery (MI)-based brain-computer interfaces (BCIs). Most current studies choose filter cut-frequencies based on…
View article: A Novel Classification Framework Using the Graph Representations of Electroencephalogram for Motor Imagery Based Brain-Computer Interface
A Novel Classification Framework Using the Graph Representations of Electroencephalogram for Motor Imagery Based Brain-Computer Interface Open
The motor imagery (MI) based brain-computer interfaces (BCIs) have been proposed as a potential physical rehabilitation technology. However, the low classification accuracy achievable with MI tasks is still a challenge when building effect…
View article: Editorial: Datasets for Brain-Computer Interface Applications
Editorial: Datasets for Brain-Computer Interface Applications Open
Montesano, & Müller-Putz, 2020). Ortega et al. collected a multimodal dataset comprising EEG, fNIRS, EMG, and movement data recorded during a force grip task (Ortega, Zhao, & Faisal, 2020).A wide range of other types of EEG-based BCIs are …
View article: Neuro-curation
Neuro-curation Open
For the past several years, museums have widely embraced virtual exhibits—certainly before COVID-19, but especially after the virus's outbreak, which has required cultural institutions to temporarily close their physical sites to audiences…
View article: Learning Common Time-Frequency-Spatial Patterns for Motor Imagery Classification
Learning Common Time-Frequency-Spatial Patterns for Motor Imagery Classification Open
The common spatial patterns (CSP) algorithm is the most popular spatial filtering method applied to extract electroencephalogram (EEG) features for motor imagery (MI) based brain-computer interface (BCI) systems. The effectiveness of the C…
View article: BCI-Based Rehabilitation on the Stroke in Sequela Stage
BCI-Based Rehabilitation on the Stroke in Sequela Stage Open
Background. Stroke is the leading cause of serious and long-term disability worldwide. Survivors may recover some motor functions after rehabilitation therapy. However, many stroke patients missed the best time period for recovery and ente…
View article: Neural and physiological data from participants listening to affective music
Neural and physiological data from participants listening to affective music Open
Music provides a means of communicating affective meaning. However, the neurological mechanisms by which music induces affect are not fully understood. Our project sought to investigate this through a series of experiments into how humans …
View article: An Optimized Auditory P300 Bci Based On Spatially Distributed Sound In Different Voices
An Optimized Auditory P300 Bci Based On Spatially Distributed Sound In Different Voices Open
In this paper, a new paradigm is presented, to improve the performance of audio-based P300 Brain-computer interfaces (BCIs), by using spatially distributed natural sound stimuli. The new paradigm was compared to a conventional paradigm usi…
View article: Novel Single Trial Movement Classification Based On Temporal Dynamics Of Eeg
Novel Single Trial Movement Classification Based On Temporal Dynamics Of Eeg Open
Various complex oscillatory processes are involved in the generation of the motor command. The temporal dynamics of these processes were studied for movement detection from single trial electroencephalogram (EEG). Autocorrelation analysis …
View article: Rapid Prototyping for BNCI Users with Cerebral Palsy
Rapid Prototyping for BNCI Users with Cerebral Palsy Open
View article: Brain-Computer Music Interfacing For Continuous Control Of Musical Tempo
Brain-Computer Music Interfacing For Continuous Control Of Musical Tempo Open
A Brain-computer music interface (BCMI) is developed to allow for continuous modification of the tempo of dynamically generated music. Six out of seven participants are able to control the BCMI at significant accuracies and their performan…