A review of critical challenges in MI-BCI: From conventional to deep learning methods
Brain-computer interfaces (BCIs) have achieved significant success in controlling external
devices through the Electroencephalogram (EEG) signal processing. BCI-based Motor …
devices through the Electroencephalogram (EEG) signal processing. BCI-based Motor …
A survey on deep learning-based non-invasive brain signals: recent advances and new frontiers
Brain signals refer to the biometric information collected from the human brain. The research
on brain signals aims to discover the underlying neurological or physical status of the …
on brain signals aims to discover the underlying neurological or physical status of the …
Memory failure predicted by attention lapsing and media multitasking
With the explosion of digital media and technologies, scholars, educators and the public
have become increasingly vocal about the role that an 'attention economy'has in our lives …
have become increasingly vocal about the role that an 'attention economy'has in our lives …
Modality-specific tracking of attention and sensory statistics in the human electrophysiological spectral exponent
A hallmark of electrophysiological brain activity is its 1/f-like spectrum–power decreases with
increasing frequency. The steepness of this 'roll-off'is approximated by the spectral …
increasing frequency. The steepness of this 'roll-off'is approximated by the spectral …
Recommendations and publication guidelines for studies using frequency domain and time‐frequency domain analyses of neural time series
Since its beginnings in the early 20th century, the psychophysiological study of human brain
function has included research into the spectral properties of electrical and magnetic brain …
function has included research into the spectral properties of electrical and magnetic brain …
A novel approach of decoding EEG four-class motor imagery tasks via scout ESI and CNN
Y Hou, L Zhou, S Jia, X Lun - Journal of neural engineering, 2020 - iopscience.iop.org
Objective. To develop and implement a novel approach which combines the technique of
scout EEG source imaging (ESI) with convolutional neural network (CNN) for the …
scout EEG source imaging (ESI) with convolutional neural network (CNN) for the …
BETA: A large benchmark database toward SSVEP-BCI application
The brain-computer interface (BCI) provides an alternative means to communicate and it has
sparked growing interest in the past two decades. Specifically, for Steady-State Visual …
sparked growing interest in the past two decades. Specifically, for Steady-State Visual …
Cortical route for facelike pattern processing in human newborns
Humans are endowed with an exceptional ability for detecting faces, a competence that, in
adults, is supported by a set of face-specific cortical patches. Human newborns, already …
adults, is supported by a set of face-specific cortical patches. Human newborns, already …
[HTML][HTML] Rethinking amblyopia 2020
DM Levi - Vision research, 2020 - Elsevier
Recent work has transformed our ideas about the neural mechanisms, behavioral
consequences and effective therapies for amblyopia. Since the 1700′ s, the clinical …
consequences and effective therapies for amblyopia. Since the 1700′ s, the clinical …
Is human face recognition lateralized to the right hemisphere due to neural competition with left-lateralized visual word recognition? A critical review
The right hemispheric lateralization of face recognition, which is well documented and
appears to be specific to the human species, remains a scientific mystery. According to a …
appears to be specific to the human species, remains a scientific mystery. According to a …